|Source: Trust Insights|
The marketing world has been going gaga over ChatGPT for the past four months.
The generative AI application from OpenAI was released to the public on November 30, 2022, and analysts have estimated that it reached 100 million monthly active users in January of this year.
The capabilities of ChatGPT have amazed many users, including me. More importantly, the buzz surrounding ChatGPT has ignited an arms race among tech companies to develop and roll out new or enhanced applications enabled by artificial intelligence.
For example, Microsoft – which had already invested $1 billion in OpenAI – recently confirmed that it will invest an additional $10 billion in the company, and announced that it is incorporating some ChatGPT-like functionality in its Bing search engine. Google, Salesforce, Hubspot, and a host of other firms have also recently announced new or enhanced applications featuring generative AI capabilities.
The application of artificial intelligence to marketing isn’t new, but the intense reaction to ChatGPT by both the public and tech companies suggests that we are on the cusp of a step change in the use of AI in marketing.
Until now, many marketers have been able to function effectively with only a superficial understanding of artificial intelligence. But, as AI becomes increasingly integral to marketing at more and more companies, it will be imperative for marketers to have a better grasp of AI principles and techniques.
Christopher S. Penn, the co-founder and Chief Data Scientist of Trust Insights, and a recognized authority on analytics, data science, and machine learning, has written a book that will help marketers begin their journey toward a better understanding of artificial intelligence.
AI For Marketers: An Introduction and Primer (Third Edition, 2021) provides a sound introduction to basic AI techniques and illustrates how AI can be used to improve marketing performance.
What’s In the Book
AI For Marketers contains 18 chapters, but the book’s content falls into four broad topic categories.
In the opening two chapters, Penn discusses the importance of AI in marketing and explains why marketers often struggle with AI. He argues that one reason marketers find AI challenging is that, ” . . . AI and its prerequisites are deeply entrenched in mathematics and statistics – two fields which are not strong points for most marketers.” (Emphasis in original)
Penn devotes four chapters to an explanation of the basic techniques of artificial intelligence. He defines AI and explains algorithms, models, and types of machine learning. He also covers the vital importance of good data and provides a useful data quality framework.
The third major topic category in AI For Marketers is a description of several practical applications of AI in marketing. Penn places his discussion in the context of problems that AI can help marketers address. For example, he explains how attribution analysis can help marketers forecast what strategies, tactics, and tools will deliver the best results, and how dimension reduction and feature selection can help marketers identify which data points are important.
Lastly, Penn discusses how companies can successfully incorporate artificial intelligence in their marketing efforts, and how marketers can prepare their careers for AI. He lays out seven steps that describe the process of becoming an “AI-first company,” and he covers the people and process governance capabilities that companies need to be successful with AI.
Writing a book about the use of artificial intelligence in marketing is a daunting task because the field is evolving so rapidly that a book can easily become outdated soon after it’s published.
Writing a book about AI for marketers is even more challenging because most marketers have little, if any, education or training in statistics or computer science, both of which are essential components of artificial intelligence.
Christopher Penn does an admirable job of addressing both of these challenges in AI For Marketers. He focuses on the core fundamentals of artificial intelligence and on the basic applications of AI in marketing. He also explains AI concepts and techniques in an informal, easy-to-understand way, making the subject accessible to marketers who haven’t been trained in statistics and computer science.
In the book, Penn argues that marketers don’t need to become practitioners of AI in the sense of learning statistics, data science, and machine learning. He uses the analogy of “chefs and farmers” to illustrate his argument. He wrote:
“Talented chefs take great ingredients and, using the right tools and skills, transform those ingredients into delicious food . . . However, what’s the likelihood that the chef is also a farmer . . . Almost none . . . [Chefs] may have some sense of what’s gone into an ingredient, but they’re not the ones to focus on the details of the ingredient’s creation . . .
The typical outcome of an artificial intelligence platform is a model that creates insights or makes decisions. The software . . . plugs into our marketing infrastructure and spits out highly refined products from the raw ingredients – data, algorithms, and analyses. The machines are the farmers, and we are the chefs.” (Emphasis in original)
I would contend that Penn’s argument goes a little too far. I believe that many marketers – particularly those in more senior roles – will need to delve a little deeper into artificial intelligence than Penn suggests.
Penn wrote that marketers “. . . should know what great data, algorithms, models, or decisions look like . . .” It’s difficult – probably impossible – to determine whether an algorithm is “great” and fit for purpose if you don’t know how the algorithm works and what its strengths and limitations are. While AI For Marketers is a solid introduction to the topic, it doesn’t go quite deep enough to provide this level of information.
Even with this one caveat, I strongly recommend Chris Penn’s book. AI For Marketers is a great resource for marketers who are beginning their journey toward a greater understanding of artificial intelligence and its expanding role in marketing.
One final point. The third edition of AI For Marketers was published in 2021 and therefore doesn’t capture the tsunami of developments in AI that have occurred over the past few months. I subscribe to Chris Penn’s Almost Timely Newsletter, and he has already provided numerous valuable insights regarding the recent developments in AI.
I have no inside information, but I suspect that a fourth edition of AI For Marketers is already in the works. In other circumstances, I might recommend that you wait a bit for the new edition of the book. But artificial intelligence is poised to become so important for marketers that I think you should read the third edition now and be prepared to read the fourth edition when it appears.